Automating the injection of believable decoys to detect snooping

We propose a novel trap-based architecture for enterprise networks that detects “silent” attackers who are eavesdropping network traffic. The primary contributions of our work are the ease of injecting, automatically, large amounts of believable bait, and the integration of various detection mechanisms in the back-end. We demonstrate our methodology in a prototype platform that uses our decoy injection API to dynamically create and dispense network traps on a subset of our campus wireless network. Finally, we present results of a user study that demonstrates the believability of our automatically generated decoy traffic. Categories and Subject Descriptors K.6.5 [Management of Computing and Information Systems]: Security and Protection—invasive software, unauthorized access; K.6.m [Management of Computing and Information Systems]: Miscellaneous—security General Terms Design, Measurement, Security Keywords Decoys, Honeyflow, Honeytoken, Traffic generation, Trapbased defense, De...

• Type: Conference
• Year: 2010
• Where: WISEC
• Authors: Brian M. Bowen, Vasileios P. Kemerlis, Pratap V. Prabhu, Angelos D. Keromytis, Salvatore J. Stolfo
• Keywords: Campus Wireless Network, Decoy Injection Api, Various Detection Mechanisms, Wireless Network, WISEC 2010